Source document: https://docs-lawep.s3.us-east-2.amazonaws.com/1698927040040.pdf (Saint Kitts and Nevis)
Although the grossing-up methods can be considered as a part of the data processing, this topic is discussed above in section 3.6.3.3.

3.6.7.1 Misclassification treatment This point is not applicable to demand side surveys collected from households/individuals.

3.6.7.2 Non-response treatment152 Introduction An important source of non-sampling error in surveys is the effect of non-response on the survey results.
Non-response can be defined as the failure to obtain complete measurements on the (eligible) survey sample.

The extent of non-response varies from partial non-response (failure to answer just one or some questions) to total non-response.

The latter case occurs when the interviewer was either unable to contact the respondent, no member of the household was able to provide the information, the respondent refused to participate in the survey or not enough information was collected in the interview (i.e.
the response is too incomplete to be useful).

This type of non-response is called unit non- response (see 3.6.7.2.1): the sample unit does not provide any of the data required by the survey.

Unit non-response is generally handled by adjusting the weight of the individuals (or households) that responded to the survey to compensate for those that did not respond.

152 References for this chapter: • Government Statistical Service (1997), Report of the Task Force on Imputation – June 1996.
Government Statistical Service Methodology Series No.

3.

London: Office for National Statistics.

• Statistics Canada (2003), Household Internet Use Survey, 2002 – Microdata User Guide.

• European Commission (2003), Household Budget Surveys in the EU: Methodology and recommendations for harmonisation 2003.

Luxembourg: Office for Official Publications of the European Communities.

• National Centre for Social Research (1999), Item non-response (different contributions).
Survey Methods Newsletter Volume 10 No.2 1999.

• Adjusting for Missing Data, Mohadjer, L., Choudhry, H., Studies of welfare populations: Data Collection and research Issues, 2001.

• Introduction to Survey Quality, Biemer, P., Lyberg, L., Wiley series in survey methodology, 2003.

• Weighting for non-response, Lynn, P., Survey and Statistical Computing, 1996.

• Non-response in the Norwegian Business Tendency Survey, Wang, J., Statistics Norway, 2004.
Methodological manual for tourism statistics — 2014, v. 3.1 172 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Partial non-response or item non-response (see 3.6.7.2.2) occurs when the respondents did not answer all questions because they did not understand or misinterpreted a question, refused to answer a question or could not recall the requested information.

Item non- response is generally dealt with by imputation.
Effect of non-response on the quality of the data Non-response – unit as well as item non-response – can seriously affect the quality of the data collected in a survey.

Firstly, the characteristics (or answering pattern) of the non- respondents can be different from those collected among the sample units who did provide eligible answers.

If such difference is systematic, serious bias can be introduced in the survey results.
Secondly, the reduction of the sample size (overall or for certain questions) will increase the variance of the estimates.

Thirdly, non-response can have an impact on the total cost of a survey exercise.

Not only because a larger initial sample may be necessary, but also because of higher unit costs of the last few percentages of respondents (due to multiple visits).

Finally, non-response can be an indicator of poor overall quality of the survey and thus create an image or confidence problem.
Minimising non-response As prevention is always better than cure, attention should be given to avoiding non- response rather than treating non-response.

The number (and timing) of reminder letters or call backs, the length of the fieldwork period, the survey technique(s) used, the length of the survey (i.e.
the response burden), the use and structure of advance letters, the dissemination of previous results or the mandatory nature of the survey can all have an impact on the number of non-contacts or refusals.

The length, design and complexity of the questionnaire, the interviewer’s training or the interviewer’s style can have an impact on the item non-response.

As this issue is common to all surveys, it will not be discussed in detail in this manual.
This chapter is mainly focussed on the treatment of non-response in the specific context of tourism demand surveys.

3.6.7.2.1 Unit non-response Introduction Unit non-response is defined as households/persons that are included in the sample but that have not participated to the survey and for which information consequently is missing for all the questionnaire variables.
Types of non-respondents include: • Non-contact • • • • Refusals Inability to respond Rejected interviews Ineligible: out-of-scope • Other ineligible • Other non-response Methodological manual for tourism statistics — 2014, v. 3.1 173 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Unit non-response can introduce bias in the survey results especially in situations in which the non-responding units are not representative of those that responded – for instance frequent travellers who are difficult to contact or persons never travelling who do not feel concerned by the topic of the survey and therefore do not participate.
Non-response increases both the sampling error, by decreasing the sample size, and the non-sampling errors.

Weighing adjustment for unit non-response The principal method for unit non-response adjustment is weighing.

Most strategies for weighting for non-response involve dividing the respondents into a set of comprehensive and mutually exclusive groups, referred to as weighting classes.

A weight is then applied to each class.


Weighing classes In order to implement non-response adjustments, it is required to create weighting classes.

It is desirable to divide the sample in "response homogeneity groups/classes".

Within these classes, the response rates should be as homogeneous as possible, and the response rate should be different among the classes.

Data used to form these classes must be available to both non-respondents and respondents.
Usually it is possible to get information about demographical (age, gender, ethnicity), geographical (urban/rural, zip code) or socio-economical (employment, income) variables from administrative data.

More advanced methods for creating weighting classes are methods like classification based on a categorical search algorithm or a logistic regression model using auxiliary variables to estimate the probability of response.
Sample-Based Weighting Adjustment In sample-based weighting adjustment, the weight adjustment applied in each class is equal to the reciprocal of the ratio of selected sample size to respondents within each of these classes (the inverse of the response rate within each class).

This non-response adjustment factor should be multiplied with the initial base weight.
A simple example: Population Sample Respondents Respondent Non- Initial Base Adjusted Adjusted (I) size (II) (III) with response Weight Base population characteristic adjustment (I / II = VI) Weight estimate (IV) Factor (V*VI=VII) (=VIII) (V = II / III) Male 8 820 000 2 100 1 600 Female 9 020 000 2 200 1 750 1 000 1 200 1.31 1.26 4 200 5 502 5 502 000 4 100 5 166 6 199 200 Total 17 840 000 4 300 3 350 2 200 11 701 200 Alternative forms of sample-based weighting are that the weights are not inverse response rates but estimated coefficients of a regression model (where survey response Methodological manual for tourism statistics — 2014, v. 3.1 174 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 is the left-side variable).
In this case, the weights are reciprocals of the estimated response rate by the regression model.

Population-Based Weighing Adjustment Population-based weighting adjustment requires population estimates and class membership of respondents.

If there is no data available about the non-respondents, population-based adjustment is still possible since this uses external control counts for the population and not data from the sample.
The method is used to correct simultaneously for both non-coverage and non-respondents.

The method is used similar to the sample-based method.

In population-based adjustment (post-stratification adjustment), the classes are created based on variables, which are known both for the respondents and the population.
Weights are then applied in proportion to the ratio of population to achieved sample, so that the sums of the adjusted weights are equal to the population totals for certain classes of the population.

A two-step procedure of first adjusting for non-response (sample-based adjusting) and then adjusting to known population counts is a commonly used method.
However, this procedure is the same as a population-based weighting adjustment if the weighting classes in the sample-based and the population-based weighting adjustment are equal.

If the strata used in the stratification are used as classes in the weighting adjustment, there is no need for the weighting adjustment.

The adjusted weighting procedure is then equal to the final grossing up/weighting procedure.
Unit non-response in tourism demand side surveys At the occasion of the metadata and quality reporting exercise for the reference year 2008, Member States were asked about the different types of unit non-response and the methods for minimising non-response or for dealing with non-response.

Overall response rates were very different across the countries/surveys, ranging from 14% to 99%.
The main reported methods for minimising non-response included prior letters (about sample inclusion), prior sending of questionnaires (this way respondents can anticipate the future filling in of the questionnaire and e.g.

keep better track of their expenditure), repeat calls, incentives, … The main reported methods for dealing with non-response included post-stratification and calibration.
3.6.7.2.2 Item non-response Introduction As already mentioned above, there are several reasons for the data being unavailable.

These include the refusal to provide an answer, the inability to provide an answer, inadequate quality of the provided answer (e.g.

implausible, incomplete, inconsistent with answers to other questions, etc.).

It can be caused by either the respondent (e.g.


refusal) or Methodological manual for tourism statistics — 2014, v. 3.1 175 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 the interviewer (e.g.

failure to record the answer adequately) but also by the survey design itself (e.g.

ambiguous routing or filtering).


If a particular questionnaire shows too many errors or if too many data are missing, it can be assumed that the household/individual in question has not co-operated satisfactorily in the survey.

The best solution is then probably to remove the household/individual from the database and adjust the weighting coefficients for the other households accordingly.
In other words, sampling units with a very high item non-response can better be classified as total non-response or unit non-response (in a category 'rejected interviews' for example).

It is however difficult to define a threshold as not all questions are equally important (i.e.

having missing data on four crucial indicators can possibly be worse than missing data on eight questions of secondary importance).
In other cases where the household/individual has supplied high-quality information for most variables but for which data on other variables are missing, the missing data can be estimated by using appropriate imputation techniques.

The imputed values are supplied in such a way as to preserve the underlying structure of the data and to ensure that the resulting records will pass all required edits or plausibility checks.
In other words, the objective is not to reproduce the true micro data value, but rather to establish internally consistent data records that yield good aggregate estimates.

Where, for a specific variable, the proportion of missing data in relation to the total number of households exceeds a certain threshold, it must be asked whether or not imputation is still suitable as this variable can probably not be used for analytical purposes.

High item non-response (e.g.


more than 20% non-response) on a specific question across several countries, can be a good reason to consider dropping or modifying the question or variable.

It should be stressed that the detection and imputation of missing data is best done by the national statistical offices (and not at Eurostat), since the national authorities best understand the local situation and might have access to auxiliary sources to improve the estimations or imputations ("subsidiarity").
Why treating non-response in the tourism demand survey?

Most methods of compensating for missing items implicitly or explicitly make the assumption that data are missing at random.

This means that the probability of an item being missing does not depend of the value of the missing item.

In the tourism demand survey, there are without any doubt systematic patterns in the occurrence of non-response.
Non-response may be higher among older respondents or lower educated respondents as they are more at risk of not understanding the questions (or not recalling the answers, such as expenditure data).

This can be taken into account by imputing within strata or classes.
But the risk of wrongly imputing the data of tourists (who feel concerned and “happily” answer the questions) to persons not participating in tourism (who drop out because they consider themselves not concerned by the survey) remains when it is the research variable itself (e.g.

participation in tourism) which may be the critical factor for the willingness or ability to provide an answer.

The logical solution to this problem would be not to impute at all.
However, non imputation does not exist as there is always an implicit imputation.

Methodological manual for tourism statistics — 2014, v. 3.1 176 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 This is obviously the case where a respondent is dropped: the status moves from item non- response to unit non-response, which will normally be solved by changing the extrapolation weight of the other respondents (and this basically comes down to a mean imputation …).
Where the statistician decides to preserve the collected data instead of imputing, the user will in most cases make an implicit imputation of the “non-stated” cases.
Let’s take the following numerical example (“did you make holiday trips during the previous quarter?”): Answering category Number of respondents (grossed up) Percentage Yes No Non-stated (missing) Total 924 000 1 980 000 1 496 000 4 400 000 21,0% 45,0% 34,0% 100,0% The proportion of persons having made holiday trips during the previous quarter can be calculated in two ways: ▪ Number of Yes answers compared to total population: 924 000 / 4 400 000 = 21,0% ▪ Number of Yes answers compared to total respondents (Yes + No): 924 000 / 2 904 000 = 31,8% Let's assume that the end-user is only interested in the proportion of tourists (and not in the percentage of non-tourists, and definitely not in the number of non-stated).
If the non- stated are mentioned separately, they will most probably be overlooked by the user or interpreted in different ways by different users – by accident or on purpose, which is not appropriate in terms of transparency and relevance of the official statistics.

Both results above suffer from silent or implicit imputation.

In the first case, the non-stated cases are treated as ‘No’ answers.
This bears the risk of overestimating the number of non- tourists: whether one has actually participated in tourism is in any case not the only factor affecting response rates in surveys on tourism demand.
In the second case, there is a risk of overestimating the number of tourists: the underlying distribution of ‘Yes’ and ‘No' answers in the ‘non-stated’ group is implicitly supposed to be identical to the distribution in the group of respondents while the incidence of not having participated in tourism is expected to be higher among the non-respondents (e.g.

because they feel less concerned by the topic).

The true value (or better: most suitable estimate) is somewhere in between, but unknown.
The easy-to-implement mean imputation (see below) will normally give exactly the same proportion of persons having participated in tourism as the case where we only take into account the respondents, but it should be remembered that this method is the ‘worst imputation scenario’ where no additional information is taken into account.

More intelligent methods would give more accurate estimates.
For example, in a postal survey, the respective response pattern of the consecutive reception waves can help fine-tuning the imputation: if response to the questionnaire is related to being a tourist or not a tourist, the questionnaires received after a first or second reminder letter will show lower participation rate.

Such digressive pattern could be introduced in the imputation process if we assume that non-response is the extreme case of a late reply.
Methodological manual for tourism statistics — 2014, v. 3.1 177 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 How to treat non-response in the tourism demand survey?

The choice of the imputation method is at the discretion of the national statistical institutes, but a number of options are briefly discussed in this section.
As experiences with the application of different methods are still missing, putting forward one particular method is not desirable at this stage.

A more detailed discussion of these and other methods is beyond the scope of this manual but can be found in the extensive literature on the issue of dealing with non-response.

Deductive methods These methods are rather related to heuristics than to modelling.
They try to deduct the most logical answer using the available information for the household or individual.

In general, such procedures will be part of the validation checks and not of the non- response treatment.

Example: the respondent did not state the main means of transport used but from his other answers, we know that it was a trip to New Zealand.

In this case, the most obvious value to impute for transport mode would be an airplane.
Imputing the mean or mode This method consists of imputing missing values by the mean observed in the group of respondents in case of numerical variables or the mode in case of categorical or binary variables.
Instead of imputing the overall mean or mode, usually, the imputation will be done taking into account some background characteristics of the household: before imputing, the respondents are grouped into different classes according to background variables such as age group, gender and educational level; the breakdown variables can however also include study variables (e.g.

destination or duration of the trip).

Within each group, the class mean or class mode is imputed to cases with missing values.
The classes may be different for each variable to be imputed.

The big advantage of this method is that it is very easy to implement and to explain.

The main drawback is that it may compress the distribution of the survey variables (as the less popular items will probably never serve as a donor).

Example: in the class ‘age group 45-54’ x ‘lower educational level’ x ‘male’, 20% of the respondents appear to have taken part in tourism during the reference quarter.
The most popular answer – in other words, the mode – is No.

Therefore, all non-respondents will be imputed with a No value (which means approximately 20% of those may be misclassified – to avoid this problem one can try the next technique).

Hot deck imputation For each respondent with a missing value for a specific variable, this value will be imputed with the corresponding value from the previous respondent in the database with a valid response on this variable.
Usually, this method is applied within classes in order to improve the quality of the imputations.

Methodological manual for tourism statistics — 2014, v. 3.1 178 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 After fixing a starting value for each item and each class, each case is processed sequentially.

If the case has a missing item, this is replaced by the imputation value from the relevant class.
If the item is not missing, it replaces the stored initial imputation value for its class, and can be used for imputation of subsequent missing items.

Closely related to this sequential hot deck imputation, is hierarchical hot deck imputation.

Here, a lot more imputation classes can be considered as the boundaries of the classes are not fixed.

When no suitable donor is found at the finest level of the classification, classes can be collapsed into broader groups until a donor is found.
Taking into account the relatively small sample sizes used in the tourism demand surveys, the hierarchical hot deck imputation may be less suitable than the sequential variant (there are probably not enough cases available to fill the high number of classes).

These methods are relatively simple to execute, assign real/existing values to a non- respondent and better respect the underlying distribution than the mean or mode imputation.
On the other hand, the algorithms may be more difficult to program (especially in the case of hierarchical hot deck) and there is a risk that one donor value is used several times (in case successive cases all show a missing value).

Nearest-neighbour imputation This method relies on being able to identify the distance between any two units based on some suitable distance measure.

Regression imputation Imputing by regression methods is usually carried out one variable at the time.
The methods require that the values of one or more auxiliary variables are known for both the complete cases on which the variable of interest is recorded and for the missing cases.

A regression model relating the variable of interest to the set of auxiliary variables is set up.

For categorical variables, particularly binary variables, logistic regression is usually used.

In this case, the imputed value will usually be the value with the higher predicted probability.
For categorical variables with many categories, this method is less suited.

For binary variables, more complex methods such as discriminant analysis could also be used.

Indicating an optimal imputation method is difficult.

The best method will depend on the data available, the nature of the survey and of course the nature of the question (binary, numerical, etc.).
However, a general rule of thumb is that the more simple methods such as mode imputation within classes or sequential hot deck do not necessary give poorer results than the advanced methods using modelling.

This argument will even be stronger when making a cost/benefit analysis (in terms of processing and programming time).
Item non-response in tourism demand side surveys At the occasion of the metadata and quality reporting exercise for the reference year 2008, Member States were asked about the variables/breakdowns that showed a significant item non-response.

About half of the countries reported item non-response exceeding 5% for the Methodological manual for tourism statistics — 2014, v. 3.1 179 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 variables relating to expenditure.
Other variables did not suffer from item non-response (i.e.

when a contact was made with the respondent, most answers were easily answered).

3.6.7.3 Computing accuracy measures The use of a sample survey unavoidably leads to sampling error.

To get an idea of the sampling error, it is advised to compute this error for certain indicators.
Such information is not only interesting to decide whether the indicator is reliable enough to be published, but this can also help to determine whether the sample size should be increased in a next edition of the survey for certain strata where a large sampling error was diagnosed.

The sampling error reflects the fact that only a particular sample was surveyed rather than the entire population.
As accuracy measure, the coefficient of variation is recommended for amounts or absolute values while the standard error (the square root of the variance) of the estimator is recommended for proportions153 (see also the metadata and quality reporting template).

The estimation of the sampling variance should ideally take into account the sampling design (e.g.

the stratification).

The computed accuracy measures will also determine the reliability of the estimates.
If the standard error for a certain proportion or absolute value is too high, the cell needs to be suppressed (not disseminated).

In case the computation of the standard error for all cells is not feasible, the number of respondents underlying the estimate can be used to decide whether a proportion can be published (e.g.

if based on less than 10 respondents, the estimate is not published).
3.6.8 Dissemination rules for micro-data files The principles laid down in this section are based on the wording/principles for EU-SILC (and LFS for wording) for paragraph (1) and Comm.

Reg 6/2003 (transport) for paragraph (2), Article 23 of Reg 223/2009 concerns "Access to confidential data for scientific purposes".

(1) The data on tourism trips and visitors making the trips, referred to in Section 2 of Annex II of Regulation (EU) No 692/2011, is based on a sample.
To avoid publication of figures which are statistically unreliable, the Commission (Eurostat) applies the following basic guidelines when disseminating aggregate tables: - an estimate shall not be published if it is based on fewer than 20 sample observations, - an estimate shall be published with a flag if it is based on 20 to 49 sample observations.
(2) Tables including estimates based on fewer than 20 sample observations may be supplied to national authorities responsible for European statistics on tourism in Member States, on 153 The (estimated) relative standard error – or (estimated) coefficient of variation (CV) – is the ratio of the square root of the variance of the estimator for the proportion to the expected value of the proportion.
It is estimated by the ratio of the square root of the estimate of the sampling variance to the estimated value.

To avoid that the level of the estimate when using the coefficient of variation has an extreme impact on the accuracy measure (e.g.

a proportion of 1% leads to a denominator of 0,01 when calculating the CV, in other words, the standard deviation is multiplied by 100), the standard deviation (i.e.

the square root of the sampling variance) should be used as a reference measure.
Methodological manual for tourism statistics — 2014, v. 3.1 180 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 condition that the national authorities apply the condition set out in paragraph 1 to any tables disseminated to other users.
(3) In applying Article 23 of Regulation (EC) No 223/2009, the guidelines set out in paragraph 1 shall also be implemented by researchers who are granted access to the micro-data files to carry out statistical analysis for scientific purposes.
Methodological manual for tourism statistics — 2014, v. 3.1 181 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7 Annexes 3.7.1 Metadata and quality reporting Drawing up reports after the execution of the survey is not only a self-assessment exercise of the work carried out by the statistical office (or any other organisation in charge of the tourism demand surveys) or a way to detect room for improvement.
Survey execution reports are also a tool for assessing the comparability from one year to another or from one country to another.

The metadata and quality reports for the tourism demand surveys coordinated by Eurostat cover the following subjects: a.
General methodological information: contact information, reference period(s); survey vehicle (where applicable); survey type; sampling unit; methodological differences compared to previous data collection exercises; timetable for the data collection process; etc… b.

Survey population: population frame used (description of the sampling frame or register used, known shortcomings of the sampling frame, ...); target population; non-target population.
c. Information on the national questionnaire (information collected that is not requirement by the EU legal basis).

d. Sampling design: sampling method; additional measures taken at the time of sampling design to improve representativeness; gross sample size.
e. Unit non-response, by giving information on: gross sample size; number of out-of- scope cases, number of other ineligible cases; number of eligible elements; number of non-contacts; number of refusals; number of cases unable to respond; number of rejected interviews; other non-response; net sample size; unit response rate.

Additionally, the reports discuss the methods used for minimizing non- response as well as the methods used for dealing with unit non-response.
f. Item non-response: variables or items with a significant item non-response rate (e.g.

above 5%); methods used for dealing with item non-response.

g. Grossing-up procedures for households.

h. Sampling error: coefficient of variation for a selected group of indicators; the calculation method for the coefficient of variation; comments on reliability, representativeness and completeness of the data.
i. Reconciliation with other data sources; coherence with mirror statistics from other countries (asymmetries?

); quality improvements undertaken compared to the previous reporting exercise.

j.

The reports include the questionnaire in national language and, if available, in English.
In cases where the recommendations provided in this Methodological Manual are not followed, the report should clearly describe deviations, the impact of those on comparability a justification for the deviation and – where possible – plans to implement the recommendations in the future.

The reporting template used for the tourism demand surveys in the European Union, including some instructions, can be found in paragraph 3.7.1.1 below.
The (draft) template covers metadata and quality indicators, which have to be reported to Eurostat within nine months after the end of the reference year.

Methodological manual for tourism statistics — 2014, v. 3.1 182 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Article 4(4) and Annex II, Section 2 Reference 3.7-1: Reg.

692/2011 concerning European statistics on tourism Article 6 – Quality criteria and reports 1.
Member States shall ensure the quality of the data transmitted.

2.

For the purposes of this Regulation, the quality criteria as laid down in Article 12(1) of Regulation (EC) 223/2009 shall apply.

3.

Every year, Member States shall provide the Commission (Eurostat) with a report on the quality of the data relating to the reference periods in the reference year, and on any methodological changes that have been made.

The report shall be provided within 9 months after the end of the reference year.

4.
4.

In applying the quality criteria referred to in paragraph 2 to the data covered by this Regulation, the arrangements for and structure of the quality reports shall be defined by the Commission in the form of implementing acts.

Those implementing acts shall be adopted in accordance with the examination procedure referred to in Article 12(2).
Reference 3.7-2: Commission Implementing Regulation 1051/2011 Annex I – Structure of quality reports Arrangements and structure for providing metadata Member States shall provide the Commission (Eurostat) with reference metadata in accordance with the Euro SDMX Metadata Structure, as defined in Commission Recommendation 2009/498/EC for the European Statistical System.
Member States shall provide the required metadata (including quality) in accordance with an exchange standard specified by the Commission (Eurostat).

The metadata shall be provided to Eurostat through the single entry point or in such a form that the Commission (Eurostat) can retrieve it by electronic means.
Contents of the metadata and quality reports The report shall include the following concepts and cover internal tourism (Annex I to Regulation (EU) No 692/2011) as well as national tourism (Annex II to Regulation (EU) No 692/2011) (1) Relevance, including completeness as compared to user needs and data completeness as compared to the requirements and recommendations laid down in Articles 2, 3, 4 and 10 of Regulation (EU) No 692/2011.
(2) Accuracy, including coverage error (over-coverage and under-coverage), recall bias, classification error, item and unit non-response (broken down by type of unit non-response), imputation rate (for Section 2 of Annex II), sampling error and coefficients of variation for a set of leading indicators and breakdowns (as well as a description of the formulae or algorithm used to calculate the coefficients of variation) and data revision (policy, practice, impact on leading indicators).
(3) Timeliness, including information on the calendar for the production process until the publication of the results (first results, final and complete results).
Methodological manual for tourism statistics — 2014, v. 3.1 183 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 (4) Punctuality, including information on the dates of transmission of the data to the Commission (Eurostat) as compared to the deadlines specified in Article 9(4) of Regulation (EU) No 692/2011 for all data deliveries relating to the reference year.
(5) Accessibility and clarity, including information on the release calendar for the main publications (paper and online) relating to the reference periods of the reference year.

(6) Comparability, including comparability between geographical areas, over time (break in series) and between statistical domains.

(7) Coherence, including coherence within the domain with data from other sources, coherence with other statistical domains, coherence between annual and infra-annual statistics.
(8) Cost and burden, including (where available) a quantitative/monetary and qualitative indication of the cost associated with the collection and production and the burden on respondents, and a description of recent or planned measures to improve cost efficiency and/or reduce respondent burden.
(9) Metadata relating to statistical presentation and statistical processing, including information on (where applicable) concepts, definitions and classifications used, sources used, population frame, target population, frequency of data collection, survey type and data collection methods, scope (and limitations to the scope), sampling design and methodology, grossing-up procedures, treatment of confidential data and disclosure control.
Metadata and quality reports (MQR) have been developed on the basis of existing reporting templates in different fields of business and social statistics within Eurostat.

They are also based on quality reporting guidelines drawn up by Eurostat's Quality Unit and on metadata templates used for the Eurostat databases on the website.

Most of the required information should be readily available in the statistical offices.
The results of the quality evaluation will also be a useful tool for internal purposes in the statistical offices.

3.7.1.1 Template for metadata and quality reports The structure presented below follows the two standardised exchange formats used in the ESS (European Statistical System): • ESMS (Euro SDMX Metadata Structure) • ESQRS (ESS Standard Quality Reporting Structure) The ESMS is user-oriented and the national metadata will be made available to users on the Eurostat website.
The ESQRS is producer-oriented and will be accessible only for partners within the ESS (after green light from the country concerned).

The templates in this section have been prepared in spread sheet format (MS Excel).

A standard web application for production and transmission of the files shall be used by the reporting countries (NRME or National Reference Metadata Editor).

Fields/concepts that are common to the ESMS and ESQRS have be filled in only once (in the ESMS).
Below is the final version (23 July 2013).

Methodological manual for tourism statistics — 2014, v. 3.1 184 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Date of the latest certification provided by the (national) domain manager to confirm that the metadata posted are still up-to-date, even if the content has not been amended.

Date of the latest dissemination of the metadata [inserted automatically by the reference metadata production system].
Date of last update of the content of the metadata [inserted automatically by the reference metadata production system].
[select date] [select date] [select date] [select date] [select date] [select date] 3.7.1.1.1 ESMS CONCEPT DESCRIPTION / COMMENTS Contact Country Contact organisation Contact organisation unit Contact name Contact person function Contact mail address Contact email address The name(s) of the organisation(s) responsible for the data collection and or other organisations involved in the data collection.

The name of the unit responsible for the metadata file (it can also include a unit number).
The name of the person responsible for the statistical domain (Ms. or Mr., first name and family name).

The title of the person responsible for the statistical domain (this title can contain the precise area of responsibility such as methodologist or data base manager).

The postal address of the person responsible for the statistical domain.

The email address of the person responsible for the statistical domain (this can be an individual mail address or a functional mailbox).
Contact phone number The phone number of the person responsible for the statistical domain.
Contact fax number [not applicable] Metadata update Metadata last certified Metadata last posted Metadata last update Statistical presentation Data description ( optional ) Classification systems Coverage - sector Statistical concepts and definitions ( optional , unless deviations from Regulation 692/2011 exist) 3.5 Statistical unit (and reporting unit) 3.6 Statistical population 3.7 Reference area ( optional , unless deviations from Regulation 692/2011 exist) 3.8 Time coverage 3.9 Base period Main characteristics of the data set described in an easily understandable manner, referring to the data and indicators disseminated.
This short description (max.

250 words, please) should be understood immediately and easily by the users.

[not applicable] [not applicable] Describe in short the main statistical variables provided.

The definition and types of variables provided should be listed.

Normally, this will coincide with the requirements in the Regulation, hence the 'optional' status.

In case there are discrepancies from the ESS/international standards, these shall be reported (not optional!)
Entity for which information is sought and for which statistics are ultimately compiled and entity reporting the information (e.g.

individual, household).

For data on participation in tourism, the statistical unit is the individual.

This means that the statistical unit will – usually – also be the reporting unit.

For collecting data on tourism trips and visitors making the trips, the statistical unit is the trip made by the individual.
In practice, the reporting unit (= the respondent selected for the interview) will report on the trip(s) made during the reference period and give the details for the different characteristics of the trip and his/her socio-demographic profile (= the visitor making the trip).

Also: target population.

The total population or "universe" of a defined class of people, objects or events.

According to Art.
According to Art.

4(c)(d) of Regulation 692/2011, this concerns all individuals residing in the territory of the Member State or country as far as participation in tourism is concerned, and all tourims trips of at least one overnight stay outside the usual environment by the resident population as far as the data on characteristics of tourism trips and visitors are concerned.

Note that a limitation to the population aged 15 and over can apply.
The country or geographic area to which the measured statistical phenomenon relates (in terms of resident population, e.g.

are all territories of the country included?).

The length of time for which data are available (e.g.

since 1996).

Please report separately for series on participation in tourism and for series on tourism trips (see also 16.2).
[not applicable] 1 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 2 2.1 2.2 2.3 3 3.1 3.2 3.3 3.4 4 5 6 6.1 6.2 7 7.1 Survey 1 Survey 2 (if applicable) The column "Survey 2" can also be used to report on the survey used to collect the data on participation in tourism (Annex II, Section 1), if different from the survey used to collect information on trips (Annex II, Section 2).
text text text text text text text text text text text text text text text text text text text text text text text text text text text year text text text year text text text text text text text text text text Unit of measure ( optional ) The unit in which the data values are measured.

In general, the unit of measure for a statistic in a table is indicated in notes with the table.

Reference period This will coincide with the reference calendar year, e.g.

"2012".
"2012".

Institutional mandate Institutional mandate - legal acts and other agreements [not applicable] Institutional mandate - data sharing [not applicable] [pre-filled] [pre-filled] Confidentiality Confidentiality - policy European or national legislative measures or other formal procedures which prevent unauthorised disclosure of data that identify a person or economic entity either directly or indirectly.
7.2 Confidentiality - data treatment (and disclosure control) Rules applied for treating the data set to ensure statistical confidentiality and prevent unauthorised disclosure.

8 8.1 8.2 8.3 Release policy Release calendar ( optional ) Release calendar access ( optional ) User access ( optional ) The schedule of statistical release dates at national level.

The policy regarding the release of statistics according to a preannounced schedule should be described.
It should also mentioned if a release calendar for the data set in question exists and if this calendar is publicly accessible.

Access to the release calendar information.

Where applicable, a link or reference to the release calendar can be given.

The policy for release of the data to users, the scope of dissemination (e.g.to the public, to selected users), how users are informed that the data are being released, and whether the policy determines the dissemination of statistical data to all users.
Methodological manual for tourism statistics — 2014, v. 3.1 185 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 9 Frequency of dissemination Dissemination format, accessibility and clarity News release Publications On-line database Micro-data access Other information collected and published at national level but not transmitted to Eurostat Regular or ad-hoc press releases linked to the data (contents, hyperlink).
Regular or ad-hoc publications in which the data are made available to the public (contents, hyperlink).

Information about on-line databases in which the disseminated data can be accessed (contents, hyperlink).

Information on whether micro-data are also disseminated (to other partners than Eurostat) Brief overview of the main additional national indicators (e.g.

coverage of age groups outside the scope of the Regulation; same-day visits; activities during the visit; etc…).
This can also include information from other sources, as long as it is published as official statistics by the NSI or equivalent ESS partner.
text text text text text text text text text text 10 10.1 10.2 10.3 10.4 10.5 11 11.1 11.2 12 12.1 12.2 13 13.1 13.2 13.3 Accessibility of documentation Documentation on methodology Quality documentation Quality management Quality assurance ( optional ) Quality assessment Relevance User needs User satisfaction ( optional ) Completeness 14 14.1 Accuracy and reliability Overall accuracy 14.2 14.3 15 15.1 Sampling error Non-sampling error Timeliness and punctuality Timeliness 15.2 Punctuality 16 Comparability 16.1 Comparability - geographical 16.2 Comparability - over time 17 Coherence 17.1 Coherence - cross domain 17.2 Coherence - internal 18 Cost and burden 19 19.1 Data revision Data revision - policy 19.2 Data revision - practice Descriptive text and references (hyperlinks) to methodological documents available.
Hyperlink(s) to documentation on procedures applied for quality management and quality assessment.

text, links text, links text, links text, links Overall assessment of data quality, based on standard quality criteria.

A qualitative assessment of the overall quality of the statistical outputs should be provided by summarising the main strengths and possible quality deficiencies.
Any trade-offs between quality aspects can be mentioned as well as planned quality improvements or achieved quality improvements compared to a previous reference year.

Main reference: "ESS Handbook for Quality Reports" (2008).

National and international (pre-filled), completeness as compared to user needs (e.g unfulfilled user needs?)
Completeness as compared to the requirements and recommendations laid down in the Regulation and Methodological Manual respectively Assessment of accuracy, linked to a certain data set or domain, which is summarising the various components.

Provide a summary of the main sources of error and an assessment of the potential for bias (sign and order of magnitude) for each key indicator in quantitative or qualitative terms as well as (where applicable) a general assessment of the sampling error.
[ESQRS report, item V.2 ] [see section 20 of this report and ESQRS report, item V.3] Length of time or time lag between data availability of the first results (even partial or provisional) and the event or phenomenon they describe: the number of days from the last day of the reference period to the day of publication of first (even partial or provisional) results on tourism trips made during the entire reference year.
This refers to the first public release regardless of the format (paper or online newsletter, automatic data upload on website, etc).

Note: see also ESQRS VI.1.1.

Time lag between the actual delivery of the data to Eurostat and the target date when it should have been delivered: the number of days between the delivery of data and the target date on which they were scheduled for delivery (i.e.

the transmission deadlines in the Regulation).

Note: see also ESQRS VI.2.1.


Measurement of the impact of differences in applied statistical concepts, measurement tools and procedures where statistics are compared between geographical areas or over time.
Describe any problems of comparability between regions, for instance because of data collection at regional level instead of national level (through regional offices) Provide information on the length of comparable time series, reference periods at which series breaks occur, the reasons for the breaks and treatments of them.

Adequacy of statistics to be reliably combined in different ways and for various uses.
The extent to which statistics are reconcilable with those obtained through other data sources or statistical domains.

Reference sources can include supply side data (f.i.

domestic nights in rented accommodation versus nights spent by residents in accommodation establishments) [not applicable] Policy aimed at ensuring the transparency of disseminated data, whereby preliminary data are compiled that are later revised.

Description of the general revision policy for the data sets.
Describe major scheduled revisions (and/or the frequency of revisions) as well as their expected average size.

As far as necessary, also minor revisions should be described.
text text text text text text text text text text text text value value value value text text text text text text text text text text Methodological manual for tourism statistics — 2014, v. 3.1 186 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 20 20.1 Statistical processing Source data 20.1.1 Source data 20.1.2 Population frame 20.1.3 Update of population frame 20.1.4 Coverage errors of population frame 20.1.5 Gross sample size 20.1.6 Net sample size 20.1.7 Sampling design and methodology 20.2 Frequency of data collection 20.3 20.3.1 20.3.2 Data collection Type of survey Data collection methods 20.3.3 Proxy interviews 20.3.4 Survey vehicle 20.3.5 Average interview time 20.4 Data validation 20.5 Data compilation 20.6 Adjustment ( optional ) Indicate if the data set is based on survey or on administrative data sources.
Information about the reference frame (population register, population census, telephone directory, register of census districts, register of dwellings, border records, administrative reference file).

Please specify the source ('owner') of the register.

Information on the last update (date) and on the usual frequency of updates (e.g.
continous, quarterly, annually) Information about known undercoverage or overcoverage of teh frame as compared to the target population, multiple listings, incorrect auxiliary information and on solutions adopted to deal with possible shortcomings or errors The finite set of individuals that is selected from the frame to be studied.

Note: in case all members of household residing in the dwelling are usually selected, the exact number of persons will not be known before the survey (f.i.
there is no connection between the register of dwellings / addresses and the register of residents), please try to estimate the number of residents on the basis of the average number of individuals per household (dwelling) obtained from the survey.

The consolidated situation should be considered, i.e.

all survey waves (four quarters, twelve months) The number of units that can be used in the final dataset (final sample size).

The consolidated situation should be considered, i.e.
all survey waves (four quarters, twelve months) Specify the methodology used (stratified sample, quota sampling, cluster sampling, two-stage sample, etc.)

Frequency with which the data are collected from the reporting units (e.g.

monthly, quarterly).

Describe the type of survey (e.g.

household survey, border survey).

Describe the method used to gather data from respondents (e.g.

postal survey, CAPI, on-line survey, etc.).


Some additional information on questionnaire design and testing, interviewer training can be provided here.

Indicate whether proxy interviews are accepted.

If so, please give an estimate of the share of units that was obtained via proxy interviews.

Indicate whether the survey is a stand-alone survey or embedded in another survey.

In the latter case, please give a short description of the survey the tourism module(s) are embedded in.
Where available, estimate of the time needed to fill in questionnaire or 'talking time' with the respondent) Process of monitoring the results of data compilation and ensuring the quality of statistical results.

Describe the procedures for checking and validating the source data and how the results of these validations are monitored and used.

Implementation of Eurostat validation rules and - where applicable- additional national rules.
Operations performed on data to derive new information according to a given set of rules.

Describe briefly the data compilation process (e.g.

data editing, imputation, weighting and grossing-up procedures, adjustment for non-response, calibration, model used etc.).

This can be seen as a summary of the ESQRS information.
21 21.1 21.2 21.3 21.4 21.5 Additional information Name of the data collection(s) in national language Name of the data collection(s) in English (if available) Questionnaire(s) in national language Questionnaire(s) in English (if available) Please enter the file name of the attached annex (if available) Please enter the file name of the attached annex (if available) Interviewer instructions in English (if applicable, if available) Please enter the file name of the attached annex (if available) 3.7.1.1.2 ESQRS CONCEPT DESCRIPTION / COMMENTS Contact Country Contact organisation Contact organisation unit Contact name Contact person function Contact mail address Contact email address The name(s) of the organisation(s) responsible for the data collection and or other organisations involved in the data collection.
The name of the unit responsible for the metadata file (it can also include a unit number).

The name of the person responsible for the statistical domain (Ms. or Mr., first name and family name).

The title of the person responsible for the statistical domain (this title can contain the precise area of responsibility such as methodologist or data base manager).

The postal address of the person responsible for the statistical domain.
The email address of the person responsible for the statistical domain (this can be an individual mail address or a functional mailbox).
text text text text text text text text value value value value text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text Survey 1 Survey 2 (if applicable) The column "Survey 2" can also be used to report on the survey used to collect the data on participation in tourism (Annex II, Section 1), if different from the survey used to collect information on trips (Annex II, Section 2).
text text ESMS report, item 1.1 ESMS report, item 1.1 ESMS report, item 1.2 ESMS report, item 1.2 ESMS report, item 1.3 ESMS report, item 1.3 ESMS report, item 1.4 ESMS report, item 1.4 ESMS report, item 1.5 ESMS report, item 1.5 ESMS report, item 1.6 ESMS report, item 1.6 I I.0 I.1 I.2 I.3 I.4 I.5 I.6 I.7 1.8 II III Contact phone number The phone number of the person responsible for the statistical domain.
ESMS report, item 1.7 ESMS report, item 1.7 Contact fax number [not applicable] Introduction (optional) Quality management A general description of the statistical process and its outputs, and their evolution over time.

text text Overall assessment of data quality, based on standard quality criteria.

A qualitative assessment of the overall quality of the statistical outputs should be provided by summarising the main strengths and possible quality deficiencies.
Any trade-offs between quality aspects can be mentioned as well as planned quality improvements or achieved quality improvements compared to a previous reference year.

Main reference: "ESS Handbook for Quality Reports" (2008).
ESMS report, item 12.2 ESMS report, item 12.2 Methodological manual for tourism statistics — 2014, v. 3.1 187 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 IV IV.1 IV.2 IV.3 Relevance User needs User satisfaction ( optional ) Completeness IV.3.1 Data completeness rate V V.1 Accuracy and reliability Overall accuracy V.2 Sampling error - values and coefficients of variation V.2.1 V.2.1.1 Sampling error - indicators Number of residents, aged 15 or over, having made at least 1 trip (for personal purpose) of at least 1 overnight stay, broken down by age group (as specified in Annex II, Section 1(C2)) V.2.1.1.1 Total (all age groups), estimated value V.2.1.1.2 Total (all age groups), coefficient of variation V.2.1.1.3 Age group 65 and over, estimated value V.2.1.1.4 Age group 65 and over, coefficient of variation V.2.1.2 Number of domestic trips during the reference year (personal & professional purpose) V.2.1.2.1 Estimated value V.2.1.2.2 Coefficient of variation V.2.1.3 Number of outbound trips during the reference year (personal & professional purpose) V.2.1.3.1 Estimated value V.2.1.3.2 Coefficient of variation V.2.1.4 Number of trips for private/personal purpose (domestic & outbound) V.2.1.4.1 Estimated value V.2.1.4.2 Coefficient of variation V.2.1.5 Number of trips for professional/business purpose (domestic & outbound) V.2.1.5.1 Estimated value V.2.1.5.2 Coefficient of variation V.2.1.6 Number of domestic trips spent at rented accommodation during the reference year V.2.1.6.1 Estimated value V.2.1.6.2 Coefficient of variation V.2.1.7 Number of domestic trips spent at non-rented accommodation during the reference year V.2.1.7.1 Estimated value V.2.1.7.2 Coefficient of variation V.2.1.8 Total expenditure of tourists during the reference year V.2.1.8.1 Estimated value V.2.1.8.2 Coefficient of variation V.2.1.9 Expenditure of tourists on accommodation during the reference year V.2.1.9.1 Estimated value V.2.1.9.2 Coefficient of variation V.2.1.10 Additional comments on sampling error, description of the formulae or algorithm used to calculate the coefficients of variation Non-sampling error V.3 V.3.1 Coverage error V.3.1.1 Over-coverage - rate V.3.2 V.3.3 Measurement error Non-response error V.3.3.1 Unit non-response - rate V.3.3.1.1 Number of ineligible units / elements V.3.3.1.2 Number of eligible units / elements V.3.3.1.3 Number of non-contacts V.3.3.1.4 Number of refusals V.3.3.1.5 Number of rejected questionnaires V.3.3.1.6 Number of other types of non-response (if any) V.3.3.1.6.1 Description, examples of other types of non-response National and international (pre-filled), completeness as compared to user needs (e.g unfulfilled user needs?)
ESMS report, item 13.1 ESMS report, item 13.1 Completeness as compared to the requirements and recommendations laid down in the Regulation and Methodological Manual respectively [not applicable] Assessment of accuracy, linked to a certain data set or domain, which is summarising the various components.
Provide a summary of the main sources of error and an assessment of the potential for bias (sign and order of magnitude) for each key indicator in quantitative or qualitative terms as well as (where applicable) a general assessment of the sampling error.

Note: "estimated value" = the actual (annual!)
figure transmitted to Eurostat using the transmission format ESMS report, item 13.2 ESMS report, item 13.2 ESMS report, item 13.3 ESMS report, item 13.3 ESMS report, item 14.1 ESMS report, item 14.1 value value value value value value value value value value value value value value value value value value value value text text value value value value value value value text value value value value value value value value value value value value value value value value value value value value text text text value value value value value value value text Please put any further information you consider useful to interpret the coefficients of variation Provide a user-oriented summary of the non-sampling error, including (where applicable) the unit non-response rate and the main variables affected by item non-response.
Divergence between the frame population and the target population.

The proportion of units accessible via the frame that do not belong to the target population.

Can be annual or for one reference period (depending on what is available), this shouldn't make a big difference.

[not applicable] Unit non-response occurs when not all elements from the target population participate in a survey.
However, not all types of non- response are taken into account when calculating the response rate as they can be related to the quality of population frame rather than to the quality of the survey data.

Note: for this report - for reasons of comparability across countries - all non-contacts are considered to be non-response of eligible cases (where in reality some of the non- contacts may concern ineligible cases).

Not applicable where administrative data sources are used (see also XII.1.1).
The consolidated situation should be considered, i.e.

all survey waves (four quarters, twelve months).

Number of units which should not be part of the coverage, out-of-scope cases (e.g.

children under 15, empty / unoccupied dwelling, non- existent dwelling (in the latter two cases please consider for each dwelling an average number of household members or inhabitants on the basis of the successful interviews).
The gross sample size minus the number of ineligible units / elements The number of selected households/individuals from the eligible units that could not be reached or never responded to the questionnaire (excluding refusals, see below).

See the note under 15.3.2.1 for teh case where dwellings/household are sampled.

The number of selected households/individuals that could be reached but refused to participate.

See the note in 15.3.2.1 for the case where dwelling/households are sampled.
The number of selected households/individuals from the eligible units that participated in the survey but whose information could not be used due to e.g.

poor quality of the information provided (e.g.

strong inconsistencies), unacceptable item-responses (most of the questions were left unanswered), survey form got lost and interview/collection can not be repeated, etc.).

See the note in 15.3.2.1 for the case where dwelling/households are sampled.
Please provide the number of households/individuals from the eligible units with other reasons for unit non-response (other than the above mentioned).
V.3.3.1.7 Total non-response V.3.3.1.8 Unit non-response rate Sum of V.3.3.1.3 + V.3.3.1.4 + V.3.3.1.5 + V.3.3.1.6 Ratio of V.3.3.1.7 / V.3.3.1.2 calculated value calculated value calculated value calculated value Methodological manual for tourism statistics — 2014, v. 3.1 188 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 text text text text text text text text text text text text text text text text ESMS report, item 19.1 ESMS report, item 19.1 ESMS report, item 19.2 ESMS report, item 19.2 text text value value value date date date date value value value date date date date V.3.3.1.9 Methods used for minimising unit non-response V.3.3.1.10 Methods used for dealing with unit non-response V.3.3.1.11 Additional comments on unit non-response V.3.3.2 Item non-response - rate V.3.3.2.1 Methods used for dealing with item non-response Please give a description of measures undertaken to maximise the response rate.
This can include e.g.

advanced notification of the participation in the survey in the form of a letter or phone call, a system of reminders of the survey participation, several contacts/visits to the respondent at different times of the day, number of attempts for phone calls, providing feedback to respondents on how the data they are providing are used, incentives.

Please indicate whether estimation methods and/or imputation methods were used for unit non-response and give a short description, e.g.
correction factor in the weighting procedure, imputation based on background characteristics known from the sampling frame, deterministic or stochastic imputation, etc.

Please put any further information which you consider to assess or interpret the information on unit non-response For which variables / breakdowns is there a significant item non- response (e.g.

> 5%)?

(f.i.
> 5%)?

(f.i.

expenditure categories, …) Please indicate which imputation techniques are used to correct for item non-response and/or which actions are undertaken to minimise item non-response (e.g.

intensive refusal conversation, …).

V.3.3.2.2 Additional comments on item non-response Please put any further information which you consider to assess or interpret the information on item non-response The ratio of the number of replaced values to the total number of values for a given variable.
Imputation is the process used to assign replacement values for missing, invalid or inconsistent data that have failed edits.

This excludes follow-up with respondents and manual review and correction (if applicable).

Thus, imputation as defined above occurs after data collection, no matter from which source or mix of sources the data have been obtained, including administrative data.

After imputation, the data file should normally only contain plausible and internally consistent data records.
For each variable where imputations were performed, the imputation rate should be reported (f.i.

if 6000 trips are in the dataset and for 300 of those the type of accommocation wes imputed by the NSI, you can write "main means of accommodation: 5%".

).

Additionally, an overall imputation rate should be reported.

Please note that also imputations of expenditure categories for package trips should be considered here.
[not applicable] Where models are applicable in relation to a specific source of error, they should be presented in the section concerned.

Policy aimed at ensuring the transparency of disseminated data, whereby preliminary data are compiled that are later revised.

Description of the general revision policy for the data sets.

Describe major scheduled revisions as well as their expected average size.

As far as necessary, also minor revisions should be described.
The average over a time period of the revisions of a key item.

The “revision” is defined as the difference between a later and an earlier estimate of the key item.

The first published annual estimate and final estimate (at the time of writing the report) should be compared.

[not applicable] Length of time between data availability and the event or phenomenon they describe.
The number of days from the last day of the reference period to the day of publication of first (even partial or provisional) results on tourism trips made during the entire reference year.

This refers to the first public release regardless of the format (paper or online newsletter, automatic data upload on website, etc).
The number of days from the last day of the reference year to the day of publication of complete and final results on tourism trips made during the entire reference year.. Time lag between the actual delivery of the data and the target date when it should have been delivered.

The number of days between the delivery of data to Eurostat and the target date on which they were scheduled for delivery (i.e.

the transmission deadlines in the Regulation).
V.3.4 Processing error V.3.4.1 Imputation rate V.3.4.2 Common units - proportion V.3.5 Model assumption error V.3.6 Data revision V.3.6.1 Data revision - policy V.3.6.2 Data revision - practice V.3.6.3 Data revision - average size V.3.7 Seasonal adjustment VI VI.1 Timeliness and punctuality Timeliness VI.1.1 Time lag - first results VI.1.2 Time lag - final results VI.2 Punctuality VI.2.1 Punctuality - delivery VI.2.2 VI.2.2.1 Overview of the survey cycle (if several survey waves, please refer to the last wave regarding the reference year, e.g.
4th quarter or December) Start of data collection period VI.2.2.2 End of data collection period VI.2.2.3 VI.2.2.4 End of data entry (all questionnaires/surveys processed and entered in the system) End of data validation (database ready for extracting results) VII VII.1 Accessibility and clarity News release VII.2 Publications VII.3 On-line database VII.3.1 Data tables - consultations VII.4 VII.5 VII.5.1 VII.5.2 VII.6 Micro-data access Documentation on methodology Metadata completeness - rate Metadata - consultations Quality documentation VII.7 Dissemination format - Other Regular or ad-hoc press releases linked to the data (contents, hyperlink).
Regular or ad-hoc publications in which the data are made available to the public (contents, hyperlink).

Information about on-line databases in which the disseminated data can be accessed (contents, hyperlink).

[not applicable] ESMS report, item 10.1 ESMS report, item 10.1 ESMS report, item 10.2 ESMS report, item 10.2 ESMS report, item 10.3 ESMS report, item 10.3 Information on whether micro-data are also disseminated.
ESMS report, item 10.4 ESMS report, item 10.4 Descriptive text and references (hyperlinks) to methodological documents available.

[not applicable] [not applicable] Hyperlink(s) to documentation on procedures applied for quality management and quality assessment.
Reference to the most important other types of data dissemination ESMS report, item 11.1 ESMS report, item 11.1 ESMS report, item 11.2 ESMS report, item 11.2 text text Methodological manual for tourism statistics — 2014, v. 3.1 189 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 VIII Comparability VIII.1 Comparability - geographical VIII.1.1 Asymmetry for mirror flow statistics VIII.2 Comparability - over time VIII.2.1 Length of comparable time series VIII.3 Comparability - domain IX IX.1 IX.1.1 IX.1.2 IX.2 Coherence Coherence - cross domain Coherence - sub annual and annual statistics Coherence - national accounts Coherence - internal X Cost and burden Measurement of the impact of differences in applied statistical concepts, measurement tools and procedures where statistics are compared between geographical areas or over time.
Describe any problems of comparability between regions, for instance because of data collection at regional level instead of national level (through regional offices) [not applicable] Provide information on the length of comparable time series, reference periods at which series breaks occur, the reasons for the breaks and treatments of them.

The number of reference years in time series from last break.

Describe any problems of comparability between domains; reconciliation with other data sources (e.g.
administrative data, data on tourism supply, mirror or partner data) Adequacy of statistics to be reliably combined in different ways and for various uses.

The extent to which statistics are reconcilable with those obtained through other data sources or statistical domains.
[not applicable] [not applicable] [not applicable] ESMS report, item 16.1 ESMS report, item 16.1 ESMS report, item 16.2 ESMS report, item 16.2 text text text text ESMS report, item 17.1 ESMS report, item 17.1 If possible, an estimate of the cost associated with the collection and production of a statistical product and an estimate of the burden on respondents.
text text XI XI.1 Confidentiality Confidentiality - policy XI.2 Confidentiality - data treatment and disclosure control European and national legislative measures or other formal procedures which prevent unauthorised disclosure of data that identify a person or economic entity either directly or indirectly.

Rules applied for treating the data set to ensure statistical confidentiality and prevent unauthorised disclosure.
ESMS report, item 7.1 ESMS report, item 7.1 ESMS report, item 7.2 ESMS report, item 7.2 XII XII.1 Statistical processing Source data XII.1.1 Source data XII.1.2 Population frame XII.1.3 Update of population frame XII.1.4 Coverage errors of population frame XII.1.5 Gross sample size XII.1.6 Net sample size XII.1.7 Sampling design and methodology XII.2 Frequency of data collection XII.3 XII.3.1 XII.3.2 Data collection Type of survey Data collection methods XII.3.3 Proxy interviews XII.3.4 Survey vehicle XII.3.5 Average interview time XII.4 Data validation XII.5 Data compilation Indicate if the data set is based on survey or on administrative data sources.
Information about the reference frame (population register, population census, telephone directory, register of census districts, register of dwellings, border records, administrative reference file).

Please specify the source ('owner') of the register.

Information on the last update (date) and on the usual frequency of updates (e.g.
continous, quarterly, annually) Information about known undercoverage or overcoverage of teh frame as compared to the target population, multiple listings, incorrect auxiliary information and on solutions adopted to deal with possible shortcomings or errors The finite set of individuals that is selected from the frame to be studied.

Note: in case all members of household residing in the dwelling are usually selected, the exact number of persons will not be known before the survey (f.i.
there is no connection between the register of dwellings / addresses and the register of residents), please try to estimate the number of residents on the basis of the average number of individuals per household (dwelling) obtained from the survey.

The consolidated situation should be considered, i.e.

all survey waves (four quarters, twelve months) The number of units that can be used in the final dataset (final sample size).

The consolidated situation should be considered, i.e.
all survey waves (four quarters, twelve months) Specify the methodology used (stratified sample, quota sampling, cluster sampling, two-stage sample, etc.)

Frequency with which the data are collected from the reporting units (e.g.

monthly, quarterly).


ESMS report, item 20.1.1 ESMS report, item 20.1.1 ESMS report, item 20.1.2 ESMS report, item 20.1.2 ESMS report, item 20.1.3 ESMS report, item 20.1.3 ESMS report, item 20.1.4 ESMS report, item 20.1.4 ESMS report, item 20.1.5 ESMS report, item 20.1.5 ESMS report, item 20.1.6 ESMS report, item 20.1.6 ESMS report, item 20.1.7 ESMS report, item 20.1.7 ESMS report, item 20.2 ESMS report, item 20.2 Describe the type of survey (e.g.

household survey, border survey).


ESMS report, item 20.3.1 ESMS report, item 20.3.1 Describe the method used to gather data from respondents (e.g.

postal survey, CAPI, on-line survey, etc.).

Some additional information on questionnaire design and testing, interviewer training can be provided here.

Indicate whether proxy interviews are accepted.

If so, please give an estimate of the share of units that was obtained via proxy interviews.
Indicate whether the survey is a stand-alone survey or embedded in another survey.

In the latter case, please give a short description of the survey the tourism module(s) are embedded in.

Where available, estimate of the time needed to fill in questionnaire or 'talking time' with the respondent) Process of monitoring the results of data compilation and ensuring the quality of statistical results.
Describe the procedures for checking and validating the source data and how the results of these validations are monitored and used.

Operations performed on data to derive new information according to a given set of rules.

Describe the data compilation process (e.g.

data editing, imputation, weighting and grossing-up procedures, adjustment for non-response, calibration, model used etc.).
ESMS report, item 20.3.2 ESMS report, item 20.3.2 ESMS report, item 20.3.3 ESMS report, item 20.3.3 ESMS report, item 20.3.4 ESMS report, item 20.3.4 ESMS report, item 20.3.5 ESMS report, item 20.3.5 ESMS report, item 20.4 ESMS report, item 20.4 ESMS report, item 20.5 ESMS report, item 20.5 XII.6 Adjustment ( optional ) text text XIII Comment Supplementary descriptive text can be attached to data or metadata Methodological manual for tourism statistics — 2014, v. 3.1 190 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7.2 Data transmission formats The general requirements for the transmission of the aggregate tables (participation in tourism, as of 2014 also same-day visits) and micro-data (trips) are contained in respectively Annex II and Annex III of Commission Implementing Regulation 1051/2011 of 20 October 2011 implementing Regulation (EU) No 692/2011 of the European Parliament and of the Council concerning European statistics on tourism, as regards the structure of the quality reports and the transmission of the data.
For the full text, see: - Annex 4.2 to this manual - http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:276:0013:0021:EN:PDF The detailed documentation on the transmission of the data is available on the extranet site CIRCABC (only for registered users, available upon request): https://circabc.europa.eu/w/browse/bf9057c9-daa4-443a-b201-7d321542f3b3 (path: CircaBC/ESTAT/tourism/Library/data_transmission) Methodological manual for tourism statistics — 2014, v. 3.1 191 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7.3 Model questionnaire for demand side surveys 3.7.3.1 Introductory remarks The aim of this model questionnaire is to propose a standard routing of the operational questions needed to gather the information to transmit to Eurostat.
The ultimate goal of the tool is to have a harmonising effect and an improved comparability of the data collected by the different national statistical institutes.

The questionnaire is a rough outline, not a ready-made questionnaire or a detailed flow for a CATI system (such exercise would not be very meaningful given that each country has its practices in questionnaire design (lay-out) and may be using a wide variety of CATI systems).

Neither is it a full package to run the survey, e.g.
announcement letters or feedback reports are very useful to increase response rates but are beyond the scope of the model questionnaire.

Furthermore, whenever deemed relevant, the questionnaire includes several options/alternatives for a question and/or routing.

Different survey tools are used: household surveys after the reference period or border/visitor surveys.

The questionnaire uses the approach of the first, given that it is the most widely spread tool (see also 3.6.4).
The questions should be understood as being directed at individuals, not at the entire household (though the latter approach is used in an important number of countries).

Ideally, the reference period is one month, in order to reduce the recall bias (see also 3.6.6, in particular Box 3.6-1).

However, since most countries use quarterly surveys (for reasons of cost-efficiency), the model questionnaire also uses a three months' reference period in the wording of the questions.
The Council and EP Regulation lays down that the scope of observation "shall be all tourism trips with at least one overnight stay outside the usual environment by the resident population and which ended during the reference period" (see Art.

4(d)), it is good practice to stress this at the beginning of the questionnaire, e.g.
for a survey in July relating to the second quarter (April-May-June): "Please do not report trips that started in June but ended in July, nor trips that started in July" "Please also report trips that started in March (or even before) and ended in April (or May/June)" and/or in the wording of the first questions: "Did you go on a tourism trip in […] and return before end of June?"
Methodological manual for tourism statistics — 2014, v. 3.1 192 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7.3.2 Questionnaire and notes 3.7.3.2.1 Part 1: Filter for non-tourists, basic information on number of trips made during the reference period Q1 During the months April, May or June, did you make domestic or outbound trips with at least one night away from home?
We are interested in trips that ended during these three months (even if started before April) and that were a non regular break from your usual environment, for professional or personal reasons - including trips to own holiday homes and non-regular visits to friends and relatives.
1 2 No Yes go to Q2 go to Q23 Q2 How many trips with at least one overnight stay did you make for personal reasons (holidays or leisure, visits to friends or relatives or other personal purpose, regardless of whether you stayed at rented or non-rented accommodation)?

|__|value if > 1 go to Q3 if ≤ 1 go to Q4 Q3 How many of those trips for personal reasons were trips abroad?
|__|value go to Q4 Q4 How many trips with at least one overnight stay did you make for professional reasons?

|__|value if > 1 go to Q5 if ≤ 1 go to Q6_Introduction Q5 How many of those trips for professional reasons were trips abroad?
|__|value go to Q6_Introduction Notes: Questions Q1 and Q2/Q4 can be combined into one single operational question: "During the months April, May or June, how many domestic and outbound trips did you make with at least one night away from home?"

(or two if the split personal/professional is kept).

 If the answer to Q2 or Q4 is 0 or 1, there is no need to ask for the number of trips abroad.
If there is only 1 trip in the reference period, the purpose will be reported during the interview, in Q6 (main purpose of the trip).

Methodological manual for tourism statistics — 2014, v. 3.1 193 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 The reason to recommend the inclusion of this extended set of questions is two-fold.
Firstly, the explicit reference in the questions to personal trips and professional trips and to the aspect of destination, will help the respondent in defining the scope (e.g.

business trips are also included) or in recalling certain less common types of trips (e.g.

domestic trips in smaller countries) that were made during the reference period.
Secondly, indicators on the number of trips in a given reference period - broken down by purpose (personal/professional) and/or destination (domestic/outbound) - are the most important indicators resulting from tourism demand side surveys.
More complete information on the number of trips made by respondents will be helpful to calibrate the results of the surveys (this can apply to adjusting the weight or the extrapolation/grossing-up factor of trips for a specific respondent as well to adjustments within the entire sample).

This is in particular the case when details on the trips are requested for only a selection of the respondent's trips during the reference period (e.g.
3 most recent trips) – this is the approach suggested for this model questionnaire (see further).

 Concerning the "usual environment" (see Q1), a detailed discussion is available in other parts of this manual.

For the purpose of a questionnaire/interview, it can be good practice to give a few typical examples (of situations that are confusing or that are easily underreported by respondents) at the beginning of the interviews.
This can be done in the format of a quick set of minimum conditions ("We are talking about trips outside the municipality, about trips with at least one night away from home.

We include trips to own residence or visits to relatives and friends") or in the format of examples ("We include: a two weeks' holiday in Italy, a two days city trip to London, a weekend in your own holiday home or in the holiday home of friends.").
3.7.3.2.2 Part 2: Characteristics of (a selection of) the trips made during the reference period – purpose, destination, duration, transport, accommodation, booking modalities What follows below in the set-up of the model questionnaire is based on the recommendation to ask the respondents to give the details of the trip only for a subset of the number of trips made during the reference period.

On the one hand, only few respondents will have made several trips (if any!)

during a reference period.


On the other hand, those few respondents who did make more than two or three trips should not be overburdened by an extremely long reporting obligation (or extremely long phone call) – usually the overall quality will not benefit from such level of burden because of survey fatigue, it can even lead to unit non-response because the respondent does not want to take a 20+ minutes interview154.
Figure 3.7-1 shows that for the EU-27 on average, less than half of the population has made one or more trips during a given reference quarter.

During the first quarter, 73% have not made any holiday trip.

This share is 63%, 50% and 68% during the second, third and fourth quarter respectively.

In other words, in all quarters, half or more of the population (and random sample?)
will not have to report any trip because no trips in-scope of the survey have been made – the situation is of course different from country to country ranging from 95% of residents of Bulgaria who did not make any trip during the first quarter to only 21% of residents of Cyprus who did not make any trip during the third quarter (data not shown in the graph).
154 Some national questionnaires foresee space to collect information on up to 9 trips during the reference period, others state that the information should be reported for each single trip.

Methodological manual for tourism statistics — 2014, v. 3.1 194 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Figure 3.7-1: Share of the population (aged 15 or over) not having made a holiday trip during the reference quarter, EU-27, 2011.
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 73% 63% 50% 68% 1st quarter 2nd quarter 3rd quarter 4th quarter Source: Eurostat, tourism statistics Notes: Estimation made for the purpose of this publication, based on data of 20 Member States, representing 77% of the EU-27 population (not including CZ, DK, IE, EL, ES, CY and PL); data extracted 10 May 2012.
Table 3.7-1 shows for one country (Austria) the distribution of the number of trips reported by respondents in the demand side survey for the third quarter of 2011 – the most important quarter during the year in terms of tourism155.

43% of the sample (n = 3507 respondents) had made neither a domestic trip nor an outbound trip (in other words, 57% had made at least one trip, regardless of the destination).
Only 3% of the respondents reported having made more than 3 trips during the reference period July-September 2011; 10% of the respondents reported having made more than 2 trips during that reference period.

Table 3.7-1: Distribution of the number of trips made per respondent during the reference quarter, Austria, Q3 2011.

# of trips Domestic trips Outbound trips Domestic and/or outbound trips respondents % cumul.

% respondents % cumul.

% respondents % cumul.
% 0 412 729 257 85 16 6 1 1 - 69% 21% 7% 2% 69% 90% 97% 99% < 0.5% 100% < 0.5% 100% < 0.1% 100% < 0.1% 100% - - 2 154 976 277 80 15 3 2 - - 61% 28% 8% 2% 61% 89% 97% 99% < 0.5% 100% < 0.1% 100% < 0.1% 100% - - - - 1 499 1 089 568 230 76 33 8 2 2 43% 31% 16% 7% 2% 43% 74% 90% 97% 99% < 1% 100% < 0.5% 100% < 0.1% 100% < 0.1% 100% (n=3507) 99% (n=3507) 99% (n=3507) 99% Source: Statistics Austria, ad-hoc request (May 2012) 155 In the third quarter of 2011, 57% of Austrians made at least one trip of one or more overnight stays, in the first, second and fourth quarter, this share of participation in tourism dropped to 28%, 37% and 31% respectively.
Methodological manual for tourism statistics — 2014, v. 3.1 195 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 This data shows that limiting the number of trips to be reported in detail by each respondent to maximum 3 will not result in a significant loss of information.
Moreover, for the few cases (in the Austrian example 3% in the main tourism demand season) where the respondent does not report on one or more of the trips in excess of the 3 already reported, the information on the total number of trips made (see Q1 to Q5) can be used to adapt the grossing up factors as needed.

The above table reflects the situation of one country only.
It is recommended to – where possible – make a similar analysis per country in order to choose the most suitable threshold of number of trips to be reported, balancing accuracy and survey cost (or respondent burden).

In case a respondent has made 1 or 2 trips during the reference period, it is recommended to collect the characteristics of all trips.

In case a respondent has made more than 2 trips, it is recommended to collect the characteristics of maximum 3 trips156.
In this latter case, it is recommended to ask the respondent to report on the three most recent trips but selecting at least one trip for personal purpose and at least one trip for professional purpose (where applicable, i.e.

in case the trips mentioned by the respondent include both types of trips, in other words if both Q2 > 0 and Q4 > 0).

Such stratification will (normally) lead to an oversampling of business trips.
However, this oversampling will be corrected via the grossing up factors (see also previous paragraph) and it will most probably lead to an increase in the quality of the data on (more rare) trips for professional purpose.

Note that in general the number of respondents that are have made business trips and have made more than 2 tourism trips in total, will be low in the sample.
Regardless of the fact that it is good practice to inform the respondent that the detail will be asked for 'only' three trips, the respondent can of course report on all trips if he/she wishes to do so.

The recommendation to ask for the most recent trips stems from a pragmatic approach but also links to the representativeness of the subset of reported trips.
The most recent trips will be the freshest in the mind of the respondent and therefore reporting on these ones only will reduce the recall bias, especially on the expenditure questions.
A possible drawback is the bias that may be induced by calendar effects: in the third quarter, there is a risk that the main holiday trip made in July or August is 'pushed away' by short(er) trips made in September outside the main season; in the first quarter, there is a risk that a (longer) trip during Christmas / New Year is 'pushed away' by short(er) trips made in February or March (however the first quarter usually has the lowest participation in tourism, see also Figure 3.7-1).
Asking for the most important trips will make sense from the point of view of the respondent ("why does the interviewer want me to report on two weekend breaks and proposes to ignore my two weeks' holiday?")

but it will induce a systematic upwards bias in the data relating to duration, expenditure and destination/distance.

156 This is a general recommendation that can be fine-tuned depending on the participation in tourism in a country.
If in a country only a very small percentage of the residents will have made more than 2 trips during a given reference period, the effect of not asking for more than 2 trips will not be significant.

The general recommendation is based on some kind of 'upper' scenario (note that the example used refer to Austria, a country with a relatively high participation in tourism: e.g.

in Q3 57% compared to 50% at EU-27 level – see Figure 3.7-1and Table 1.4-1).
In case of a reference period of one month instead of three months, it could be sufficient to give detailed answers for the most recent one or two trips only; again it will be necessary to make an assessment of the information (and accuracy) lost compared to a design where all trips during the reference period are reported in detail.
Methodological manual for tourism statistics — 2014, v. 3.1 196 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Randomly selecting the subset of trips possibly introduces an element of recall bias (if the reported trips took place two or three months before the interview) and would necessitate the preparatory work of listing all the trips.
Q6_Introduction If Q2 + Q4 = 1 "Now I would like to ask some more detailed questions concerning this trip" If 1 ≤ Q2 + Q4 ≤ 3 "Now I would like to ask some more detailed questions concerning each single trip" If (Q2 > 3 and Q4 = 0) or (Q2 = 0 and Q4 > 3) "Now I would like to ask some more detailed questions concerning the three most recent trips" If (Q2 + Q4 > 3) and (Q2 > 0) and (Q4 > 0) "Now I would like to ask some more detailed questions concerning the three most recent trips, at least including one trip for private purpose and one for professional purpose (even if less recent, but still ended in April, May or June)" go to Q6 Q6 FILTER: if Q2 = 0 go to Q7 What was the main purpose of the trip?
Personal, for visiting friends and relatives Personal, for leisure, recreation and holidays 1 2 3 Other personal purpose (e.g.

pilgrimage, health treatment on medical advice, …) 4 Business or professional go to Q7 Q7 What was the country of destination (where did you spend most of your stay)?
1 <Own country> 2 <First ranked foreign country> 3 <Second ranked foreign country> 4 <Third ranked foreign country> 5 <Fourth ranked foreign country> 6 <Fifth ranked foreign country> other, please specify: |_____________|country go to Q8 Methodological manual for tourism statistics — 2014, v. 3.1 197 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q8 FILTER1: if Q6 = 2 or Q6 = 3 or Q6 = 4 go to Q9 FILTER2: if year ≠ 2013 go to Q9 What features of the destination or places you visited attracted you to go there?
Multiple answers can be ticked.

1 City 2 Seaside 3 Countryside, including lakeside, river, etc.

4 Cruise ship 5 Mountains (highlands, hills, etc.)

6 Other go to Q9 Q9 What was the month of departure of the trip?

1 June 2 May 3 April 4 March other, please specify: |_____________|month(+year) go to Q10 Q10 How many nights did you spent away from home on this trip?
|__|value go to Q11 Q11 FILTER1: if Q7 = 1 go to Q12 FILTER2: if year ≠ 2013 go to Q12 On this trip abroad, how many nights (if any) did you spent away from home on domestic territory before leaving the country?
|__|value go to Q12 Methodological manual for tourism statistics — 2014, v. 3.1 198 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q12 FILTER1: if Q6 = 4 go to Q13 FILTER2: if year ≠ 2013 go to Q13 Did the travel party include children under 15 years?

The travel party is the group of persons with whom you decided to take the trip and with whom you shared a common budget.
1 Yes 2 No go to Q13 Notes: The sequence of the questions is "purpose", then "destination" and then "duration" for reasons of routing/filtering.

The second question on destination (type of destination, Q8) only applies to trips for personal purpose (Q6); the second question on duration (nights on domestic territory, Q11) only applies to outbound trips (Q7).
In the case of a paper or web questionnaire, it is recommended to pre-print tick boxes for the most popular tourism destinations (see Q7).

This will make the survey easier to complete for a big majority of the respondents (while those we did not visit one of the most popular destinations can still make use of the "Other, please specify" option).

Together with the home country (domestic trips), the top 5 or top 10 most popular destinations will usually cover the vast majority of the tourism trips.
See Table 3.7-2 on the next page: domestic trips represent in all countries the biggest share of tourism trips, ranging from 63% in Lithuania to 94% in Romania ; in all countries, the domestic trips plus the trips to the top 5 foreign destinations represent 80% or more of the total number of (holiday and business) trips ; in all countries, the top 5 foreign destinations account for roughly half of all outbound trips.
For the country of destination (Q7), it is recommended to brief the interviewer (or the respondent via explanatory notes next to the question in a paper questionnaire) on some popular sub-national destinations, e.g.

Mallorca, Canary Islands = Spain, Crete = Greece, etc.

(alternatively, the respondent can write down the destination and leave the appropriate recoding for the data entry stage at the statistical office).
This questionnaire asks for the main country destination of the trips (see also 3.4.3).

Notwithstanding what is laid down in Regulation 692/2011, national statistical authorities can collect information on the region(s) visited within the country during domestic trips or ask for all countries visited during the trip (e.g.

to improve usefulness of tourism statistics for compilers of the BoP Travel item – some NSIs ask for each visited country on a trip the duration of the stay and/or expenditure).
Both extensions are out of the scope of this Manual.

 The decision to visit a specific destination can be made on the basis of bundle of characteristics and not one specific element, therefore respondents are allowed to tick more than one answer in Q8 (or better: tick all answers that apply).

See also 3.4.5.

 In Q9 the three months of the reference period as well as the month preceding the reference month are presented as tick boxes, for the ease of the respondent.
Methodological manual for tourism statistics — 2014, v. 3.1 199 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q9 and Q10 are sufficient to collect the information needed for variables A1 (month of departure) and A2 (duration of the trip) in the Regulation.

An alternative is to ask for exact dates of departure and return.
While the latter approach perhaps gives more precise information, it can be difficult for the respondent to answer (does he/she have a calendar lying next to the phone?)157.

 For Q10 (and Q11), nights spent on the trip before the reference period started obviously have to be included (e.g.

25 March – 4 April = ten nights, not three nights).

 Q8, Q11 and Q12 cover information that needs to be sent to the Commission (Eurostat) only every third year, starting in 2013 (2016, 2019).
When countries collect the information on an annual basis, they are encouraged to send the data to Eurostat each year (compulsory as well as optional variables are included in the same transmission format (see also 3.7.2).

Table 3.7-2: Share of domestic trips and trips to main foreign destinations in total tourism trips, 2010, selected European countries.
Share of domestic trips in total tourism trips Share of domestic trips + top5 foreign destinations in total tourism trips Share of top5 foreign destinations in total outbound tourism trips Top5 foreign destination countries DK DE ES FR IT LT HU PL PT RO SK SE UK NO HR Source: Eurostat, tourism statistics (data extracted May 2012) 55% 51% 55% 47% 48% 44% 48% 45% 60% 58% 50% 47% 50% 56% 46% SE, DE, ES, NO, UK AT, IT, ES, FR, NL FR, IT, PT, UK, DE ES, IT, UK, DE, BE ES, FR, UK, DE, AT LV, PL, DE, UK, RU DE, AT, CZ, RO, IT DE, UK, IT, FR, ES ES, FR, UK, DE, BR IT, HU, ES, EL, DE CZ, IT, HU, BG, AT FI, DE, EL, DK, NO ES, FR, US, IE, IT SE, DK, ES, UK, DE DE, AT, IT, SI, HU 157 The Spanish FAMILITUR tourism demand survey does ask for the detailed dates, reportedly without any important problems.
The survey mode may play a role: in a paper questionnaire, the respondent has more time to digest the question and look up some of the missing information, as compared to a telephone interview.

Methodological manual for tourism statistics — 2014, v. 3.1 200 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q13 What was the main means of transport?
We are interested in the transportation mode that was used to get to the destination and that covered the longest distance.

Train 1 Air 2 Ship (passenger line and ferry, cruise, yacht, rented vessel, etc.)

3 4 Bus, coach (scheduled or non-scheduled) 5 Motor vehicle (private or rented, e.g.

car) 6 Other (e.g.
car) 6 Other (e.g.

bicycle) go to Q13B Q13B FILTER: if year ≠ 2014 go to Q14 Did you book the main means of transport via a tour operator or travel agency?

This also includes online tour operators and travel agencies (such as Expedia.com or Booking.com).

1 Yes 2 No 3 Don’t know go to Q13C Q13C Did you book the main means of transport online?
We are interested in whether the transport was booked via online forms or online reservation systems on the service provider’s website, or via online tour operators or travel agencies.

This does not include manually typed e-mails or phone calls over the internet.
1 Yes 2 No 3 Don’t know go to Q14 Methodological manual for tourism statistics — 2014, v. 3.1 201 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q14 What was the main means of accommodation?

If you were accommodated at several types of accommodation during the trip, please indicate the one you were mainly accommodated at, i.e.

most of the nights.
most of the nights.

1 Hotels or similar accommodation (where services typically include daily cleaning and bed-making) 2 Campsites, caravan or trailer park (non-residential) 3 Other rented accommodation (even if you didn't pay it yourself), including youth hostels, holiday homes, apartments, bungalows, marinas, health establishments, etc.
4 Own holiday home, second home 5 Accommodation provided free of charge by relatives or friends 6 Other non-rented accommodation go to Q14BQ14BQ14BQ14BQ14BQ14BQ14B Q14B FILTER1: if year ≠ 2014 go to Q15 FILTER2: if Q14 = 4 or Q14 = 5 go to Q15 FILTER3: if Q14 = 6 go to Q14C Did you book the main means of accommodation via a tour operator or travel agency?
This also includes online tour operators and travel agencies (such as Expedia.com or Booking.com).

1 Yes 2 No 3 Don’t know go to Q14C Q14C Did you book the main means of accommodation online?

We are interested in whether the accommodation was booked via online forms or online reservation systems on the service provider’s website, or via online tour operators or travel agencies.

This does not include manually typed e-mails or phone calls over the internet.
1 Yes 2 No 3 Don’t know go to Q14D Methodological manual for tourism statistics — 2014, v. 3.1 202 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q14D FILTER: if Q13B ≠ 2 or Q14B ≠ 2 go to Q15 You indicated that no tour operator or travel agency was used to book the main means of transport and accommodation.
Was the trip arranged independently because: 1 Transport and/or accommodation services were booked directly with the service provider (including booking upon arrival at the reception or ticket office) ; or 2 No booking was needed for transport and accommodation (e.g.

own transport, non-rented accommodation) go to Q15 Notes: Q13 and Q14 collect information on the main means of transport and on the main means of accommodation respectively.
Some national surveys collect information on more than one means of transport/accommodation (for national purposes), ranked by order of importance.

 For Balance of Payments (travel item) compilers, it is not only relevant to know the means of transport (and the related expenditure), but also the economy to which the service provider belongs.

For BoP purpose, the entire amount spent on a trip does not necessarily create a debit situation vis-à-vis the foreign country visited.
This is especially the case where a domestic carrier was used to get to the destination by plane.

When the tourism demand survey is also used for Balance of Payments compilation, it is recommended to insert an additional question when Q13 = 1 (i.e.

transport by air), namely whether the respondent used a national carrier (a list of the main companies can be given as examples).
Q14 can be split in two parts, first asking whether the accommodation was rented or non- rented and then offering the suitable answering options within the relevant category158.

It is recommended anyway to ask for the expenditure for accommodation in all situations, for validation and consistency purposes.

 Q13 and Q14 both have follow-up questions to collect, every third year (i.e.

reference year 2014, 2017, etc), the information on the booking modalities (see 3.4.9).
Instead of grouping the questions relating to the booking of the trip in a separate module, this model questionnaire groups the questions relating to transport (Q13B and Q13C) with the annual question on main means of transport and the questions relating to accommodation (Q14B and Q14C) with the annual question on main means of accommodation.
Putting the booking related questions right after the main question should also facilitate understanding that the booking also refers to the main means of transport or accommodation.

158 Bear in mind that this approach can not be used as a filter for the expenditure questions (when non- rented accommodation is ticked, i.e.

Q14 = 4, 5 or 6).
Q14 = 4, 5 or 6).

The question on expenditure for accommodation can not be omitted in case the main means of accommodation was non-rented accommodation, possibly some nights were spent at rented accommodation too.

Only for trips with a duration of one night the filter/routing could be applied.
Methodological manual for tourism statistics — 2014, v. 3.1 203 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q14B includes a filter to route respondents who stayed at their ‘own holiday home’ or at ‘accommodation provided for free by relatives or friends’ to the next question (as no booking of accommodation was needed for these trips).
Note that respondents who stayed at ‘other non-rented accommodation’ are nevertheless routed to the question on booking via the internet (to cover the case of websites offering its users/members hospitality exchange services, e.g.

house swapping or couch surfing).

 Q13B does not include a filter, but when the spontaneous answer of the respondent to Q13 is ‘my own car’ or ‘private car’, it is obvious that the interviewer can re-route the respondent to Q14 instead of asking Q13B and Q13C.
Alternatively, explicitly splitting the category "motor vehicle" of Q13 into 2 categories - "private motor vehicle" and "rented motor vehicle" - can give interesting stand-alone information (note that in 2012 for 65% of all trips at EU-28 level "motor vehicle" was reported as the main means of transport) as well as make it possible to route respondents more efficiently through Q13B and Q13C (see further).Q14D is a follow-up question to both Q13B and Q14B, namely to ask about the type of independent booking in case no travel agency or tour operator was used to book the main means of transport or the main means of accommodation.
Note that the answering options have been slightly reworded from the categories listed in the Annex to Regulation 692/2011, this in order to align the model questionnaire with the guidelines/recommendations given in section 3.4.9.4.
Instead of the currently presented structure, certain Member States have used other ways of presenting this set of questions to the respondents (with potential savings in terms of interview length), for instance: a. Q13 (including a split of "motor vehicle" in private or rented) – those who answered "private motor vehicle" are not routed to the following two questions b. Q13C (asking whether the means of transport was booked online or not) c. Q13B (asking whether the transport was booked via a TO/TA) d. Q14 – those who answered "own holiday home, second home" or "accommodation provided free of charge by relatives or friends" are not routed to the following two questions e. Q14C (asking whether the means of accommodation was booked online or not) f. Q14B (asking whether the accommodation was booked via a TO/TA).
This approach will be further explored until the next compulsory reference year for these triennial variables.

 Under certain assumptions the information collected in Q14D can be derived from the other questions.
These assumptions include that the only means of transport for which no booking would be needed is "private motor vehicle" and that the only means of accommodation for which no booking would be needed are "own holiday home, second home" and "accommodation provided free of charge by relatives or friends".
The extent to which this hypothesis holds be tested using the data for the reference year 2014 (first inclusion of these triennial variables) and if sufficiently positive the model questionnaire and guidelines will be adapted accordingly.

 The booking modalities also include a (triennial) variable relating to whether or not the trip was a package trip.

This information is collected via Q15 and Q17 (see below, 3.7.3.2.3).
Methodological manual for tourism statistics — 2014, v. 3.1 204 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7.3.2.3 Part 3: Characteristics of (a selection of) the trips made during the reference period – expenditure As mentioned in paragraph 3.4.10.5.3 (Individual expenditure versus travel party expenditure), Regulation 692/2011 lays down a transmission of individual expenditure on the trip, not the grouped expenditure for the entire household or travel party.
However, when collecting the data, the respondent can be asked for individual expenditure or for the total expenditure for the travel party – depending on what is perceived as the easiest option for the respondent.

For the data collected under Directive 95/57, both approaches have been used by the EU Member States.

This model questionnaire uses the approach of the expenditure for the individual (the respondent).
Two alternative versions – group expenditure or a mixed approach - are also included, in these two alternatives additional questions need to be included on the number of persons in the travel party (and the number of children in the travel party, to make the estimate of the individual expenditure more accurate – see also footnote 144 on so-called equivalence scales).
Paragraph 3.4.10.5.4 touched the issue of package trips and the difficulty of collecting information on the components of the package from respondents159.

It is recommended to ask the respondent for the amount paid for the package and apply a model to estimate the amount for each component (see also 1.4.5 for further information/practices on unbundling packages).

The model questionnaire asks for the amounts in euro.

Obviously this should be adapted to the national situation (i.e.
the currency of the country of residence).

Q15 The next set of questions refers to the expenditure you made for this trip.

Please think only of the expenditure for your person; in case of shared expenditure – fully or partially – please try to estimate your share.

Was part (or all) of the expenditure for the trip paid to a travel agency or tour operator in the context of a package trip?
1 2 No Yes go to Q16 go to Q18 Q16 How much did you pay for the package to the travel agency or tour operator?

€|________|value go to Q17 159 Data for 2010 (Directive 95/57) shows that on average for the countries where data on package trips is available, 15% of all holidays trips of four nights and more were package trips, ranging from less than 5% in Latvia, Portugal and Croatia to more than 25% in Estonia, Austria and Slovakia.
Methodological manual for tourism statistics — 2014, v. 3.1 205 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q17 What components did the package fully or partially cover?

Tick all that apply.

1 Transport 2 Accommodation 3 4 Other goods or services (e.g.

excursions, courses, entrance fees, wellness, …) Food and drinks in cafés and restaurants (e.g.
half board, full board, all inclusive) In the next questions, please indicate what you spent in addition to the package on the different components (answer zero if the component was entirely covered by the amount paid for the package) go to Q18 Q18 How much did you spend on transport?

Think of local and international transport, car rental, fuel, road tolls, etc.

€|________|value go to Q19 Q19 How much did you spend on accommodation?
€|________|value go to Q20 Q20 How much did you spend on food and drinks in cafés and restaurants?

€|________|value go to Q21 Q21 How much did you spend on other services or goods?

Think of goods for personal use, entrance fees to museums or events, sightseeing, courses (diving, cooking, etc.

), health or wellness, etc.

This can also include durables and valuable goods.


€|________|value if > €300, go to Q22 if ≤ €300, return to Q6 (to report another trip) or go to Q23 Methodological manual for tourism statistics — 2014, v. 3.1 206 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q22 How much of the amount relates to durable and valuable goods?

Think of valuable goods such as paintings, jewellery or durable consumer goods such as computers, cameras.
Exclude typical souvenirs of limited monetary value.

€|________|value return to Q6 (to report another trip) or go to Q23 Notes: In this model questionnaire, only the main components and a 'closing category' other is asked.

The respondent is not asked for the total amount.

In a paper questionnaire, this would be an unnecessary burden.
In a telephone (CATI) survey or in an online survey, it is recommended to (automatically) calculate the total and present outcome to the respondent for verification ("So I can conclude that the total expenditure on this trip was approximately <…> euro"?).

Notwithstanding this, it is recommended to include a closing question asking for the total expenditure on the trip in cases where item non-response on the expenditure questions is very significant.
This additional question will help to retrieve some of the information that would be lost when a respondent only has an idea about the total but not about the contribution of each component; starting for the estimated total, the categories can be imputed by using the information obtained for similar trips made by other respondents.
Ideally, information should be collected on the country of residence of the tour operator or travel agent from whom the package was purchased (see also §4.36(c) of the IRTS 2008).

However, this necessitates additional questions that can be difficult for the respondent to answer.

A trade-off needs to be made between additional burden and additional relevance of the expenditure data (e.g.

for TSA or BoP purposes).

 Q15 refers to “a travel agency or tour operator”.
Note that the package can also be booked via a non-profit organisation that the respondent is a member of.

See also 3.4.9.1.2.

This also applies to the wording of Q16, Q15A3 and Q15B4 (see further).

 Q17 is included to allow for more accurate estimations of the different components of the amount paid for the package afterwards160.

The respective amounts on accommodation, transport, etc.
to be transmitted to Eurostat will be the sum of the unbundled part of Q17 and the additional expenditure reported in respectively Q18, Q19, etc.

160 This question can also reveal inconsistencies in the answer on Q15, namely when the minimum elements of a package trip are not among the reported components (the respondent only ticked "other goods or services" (e.g.

a one week diving class) without transport or accommodation being included in the package).
In such cases, interviewers might need to re-route and/or give further explanations on package trips.

Methodological manual for tourism statistics — 2014, v. 3.1 207 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 In Q21, the routing threshold of €300 is purely arbitrary161.

The purpose of the threshold is to avoid that a respondent who spent only a relatively small amount on other goods or services is routed to an additional question.
If one has spent only €300 on other goods or services, it is not very likely that this amount will include valuables or durable goods.

The threshold can be refined by taking into account the duration of the trip (i.e.

the information collected in question Q10).


 At the end of the module on expenditure (also the last module collecting information on the characteristics of the trip), the respondent should be re-routed to Q6 (first question collecting information on the characteristics of the trip) in case details on other trips need to be reported, or to Q23 (to start of the module on the profile of the visitor).
In case the respondent is not asked for his/her individual expenditure on the trip but rather on the expenditure of the entire travel party (or household), Q15 can be replaced as follows: Q15A1 The next set of questions refers to the expenditure you made for this trip.

Please include the expenditure for all members in the travel party (this is the group of persons with whom you decided to take the trip and with whom you shared a common budget).
How many members (including you) were in the travel party?

|__|value go to Q15A2 Q15A2 FILTER1: if Q12 = 2 go to Q15A3 FILTER2: if Q15A1 = 1 go to Q15A3 How many members of the travel party were younger than 15 years?

|__|value go to Q15A3 Q15A3 Was part (or all) of the expenditure for the trip paid to a travel agency or tour operator in the context of a package trip?
1 2 No Yes go to Q16 go to Q18 161 A previous version of this Manual suggested a threshold of 100 euro.

Following an exchange of views on the experiences in the first reference year at the occasion of the Task Force on Tourism Statistics, it was agreed to revise this recommended threshold upwards to 300 euro.
Methodological manual for tourism statistics — 2014, v. 3.1 208 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Another alternative is to leave it up to the respondent to report individual expenditure or group (travel party) expenditure.

In this case, Q15 can be replaced as follows: Q15B1 The next set of questions refers to the expenditure you made for this trip.
Please indicate whether you prefer to answer for your own expenditure only or - if applicable - for the expenditure by the entire travel party (this is the group of persons with whom you decided to take the trip and with whom you shared a common budget, e.g.

your household).
your household).

Individual expenditure 1 2 Expenditure of the entire travel party go to Q15B4 go to Q15B2 Q15B2 How many members (including yourself) were in the travel party |__|value go to Q15B3 Q15B3 FILTER1: if Q12 = 2 go to Q15B4 FILTER2: if Q15B2 = 1 go to Q15B4 How many members of the travel party were younger than 15 years?
|__|value go to Q15B4 Q15B4 Was part (or all) of the expenditure for the trip paid to a travel agency or tour operator in the context of a package trip?
1 2 No Yes go to Q16 go to Q18 Methodological manual for tourism statistics — 2014, v. 3.1 209 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 3.7.3.2.4 Part 3: Profile of the visitor (socio-demographic characteristics) Variables A20 to A25 in the Regulation collect information on the profile of the visitor.
The construction of the variables (and corresponding questions below) is to the extent possible based on the Core Social Variables commonly used in European social statistics162.

Typically, not all questions will have to be collected directly from the respondent.

Information can be available from the register that the sample was taken from (in particular age or sex of the respondent) or information can be available from another survey that the tourism demand survey is embedded in (e.g.
employment situation or educational attainment level).

Nevertheless, all variables/questions (also those that are optional in the Regulation) are included here, for reasons of completeness163.

In this model questionnaire, the part relating to the profile of the visitor is put at the end of the set of questions.

This was done in order to put sensitive questions like the household income (or employment situation) towards the end to avoid respondent drop-out.
Where respondents are less likely to be 'offended' by this type of questions (or where these voluntary questions are not included), the socio-demographic questions can also be put at the beginning of the survey as a "warming up".

Q23 FILTER: if respondent's sex is known (e.g.

sample from population register) go to Q24 Sex?

1 Male 2 Female go to Q24 Q24 FILTER: if respondent's age is known (e.g.

sample from population register) go to Q25 Age?
|__|value go to Q25 162 For more background information, see the final report of the Task Force on Core Social Variables: http://ec.europa.eu/eurostat/documents/3859598/5901513/KS-RA-07-006-EN.PDF/71481ffb-771a- 489b-a749-1a055c0247d4?version=1.0 163 Except variable A22 "Profile of the visitor: country of residence" as this is simply the country collecting the information (see also 3.4.13).
Methodological manual for tourism statistics — 2014, v. 3.1 210 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Q25 FILTER: this is an optional variable (A24) in Reg.

692/2011, if not included go to Q26 How would you describe your employment situation or your occupation?
Employed (employee, self-employed) 1 2 Unemployed 3 Student, pupil 4 Other not in the labour force go to Q26 Q26 FILTER: this is an optional variable (A23) in Reg.

692/2011, if not included go to Q27_Introduction What is your highest educational attainment level (completed)?
1 At most lower secondary 2 Upper secondary and post-secondary (non-tertiary) 3 Tertiary go to Q27_Introduction Q27_Introduction FILTER1: this is an optional variable (A23) in Reg.
692/2011, if not included END FILTER2: if respondent is willing to report estimate of household income go to Q27A if respondent prefers not to give details, try band/quartiles go to Q27B Q27A Q27B Can you give an estimate of the net In which of the four following ranges monthly income of the household?

would you estimate your net monthly This includes salaries (after taxes and household income?
This includes salaries social security contributions, but (after taxes and social security contributions, including benefits), regular bonuses, but including benefits), regular bonuses, income from self-employment, income from self-employment, allowances allowances such as unemployment such as unemployment benefit, pension, etc.

benefit, pension, etc.


|_|_|_|_|_|_|_|value go to END Less than €1000 1 2 Between €1000 and €1999 3 Between €2000 and €3999 4 €4000 or more go to END Methodological manual for tourism statistics — 2014, v. 3.1 211 The demand side: Participation in tourism, Tourism trips and visitors, Same-day visits 3 Notes: The inclusion of employment situation (Q25), education level (Q26) and household income (Q27A/Q27B) is not obligatory (according to Reg.

692/2011).
692/2011).

While this is relevant information in terms of the profile of the visitor (both for business users as for government users), it can be considered as of secondary importance compared to the characteristics of the trip.

It is strongly recommended to include this information in the tourism demand databases if it is available from registers or from the survey vehicle used for the surveys.
Educational level (Q26) refers to the ISCED classification (recently revised), it is recommended to use labels that are closer to the national education system (correspondence tables are under preparation and will be disseminated via the Eurostat website) – see also 3.4.14).

 The quartiles used in Q27B are purely arbitrary.

The ranges will differ from one country to another.

It is recommended to give realistic ranges (i.e.


ranges actually dividing the sample – or grossed up sample – into four groups of more or less equal size), using existing statistics from EU-SILC, the Labour Force Survey or the Structure of Earnings Survey.

For reasons of readability of the questionnaire, it is of course recommended to round to the border values to the nearest 'round figure' (e.g.

"€4000 or more" instead of the more accurate and more uniformly distributed ""€3879 or more").
3.7.3.2.5 Part 4: Participation in tourism A stand-alone module to collect the information on the participation in tourism can be found in 3.3.1.1 on page 118.

In many countries, this information is collected by means of an extra module in the quarterly tourism demand survey referring to the last quarter of the year (this module having a reference period of twelve months).

The advantage is two-fold.

Firstly, the concepts (tourism, trip, etc) are already known to the respondent.
Secondly, some questions can be omitted by re-using information obtained elsewhere in the interview, e.g.

if the respondent made a long domestic trip during the last quarter, it is no longer necessary to ask if he/she made such trip during the entire year – the answer is obviously 'yes'.
Methodological manual for tourism statistics — 2014, v. 3.1 212 EU legislation 4 4 EU legislation 4.1 Regulation and amendments 4.1.1 Regulation (EU) No 692/2011 of the European Parliament and of the Council of 6 July 2011 concerning European statistics on tourism http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:192:0017:0032:EN:PDF Methodological manual for tourism statistics — 2014, v. 3.1 213 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 214 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 215 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 216 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 217 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 218 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 219 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 220 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 221 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 222 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 223 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 224 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 225 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 226 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 227 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 228 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 229 EU legislation 4 4.2 Delegated acts 4.2.1 Commission Delegated Regulation (EU) No 253/2013 of 15 January 2013 amending Annex II to Regulation (EU) No 692/2011 of the European Parliament and of the Council, as regards adaptations following the revision of the International Standard Classification of Education ISCED in relation to the
 variables and breakdowns to be submitted Text with EEA relevance http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:079:0005:0006:EN:PDF Methodological manual for tourism statistics — 2014, v. 3.1 230 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 231 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 232 EU legislation 4 4.3 Implementing measures 4.3.1 Commission implementing Regulation (EU) No 1051/2011 of 20 October 2011 implementing Regulation (EU) No 692/2011 of the European Parliament and of the Council concerning European statistics on tourism, as regards the structure of the quality reports and the transmission of the data http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:276:0013:0021:EN:PDF Methodological manual for tourism statistics — 2014, v. 3.1 233 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 234 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 235 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 236 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 237 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 238 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 239 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 240 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 241 EU legislation 4 Methodological manual for tourism statistics — 2014, v. 3.1 242 EU legislation 4 4.3.2 Commission Implementing Regulation (EU) No 81/2013 of 29 January 2013 amending Implementing Regulation (EU) No 1051/2011 as regards the micro-data files for the transmission of data http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:028:0001:0002:EN:PDF Methodological manual for tourism statistics — 2014, v. 3.1 243 EU legislation 4 Methodological manual for tourism statistics — 2014,
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